基于学科理解的电功视角下“化学反应与能量”教学

基于教师对电化学反应与能量的学科理解，抽提和凝练本原性问题：系统与环境之间的能量传递形式只有“热”吗?电化学反应如何实现电功传递?通过“电功”视角下认识化学反应与能量的主题大概念教学设计与实施，帮助学生建构和完善“电功”认知模型，应用模型进行探究和迁移，形成电化学主题特质性思维方式和方法，充分落实化学学科核心素养。     

利用减秩因子分析法同时优化确定化学反应级数和速率常数

通过对反应过程中在线测得的动力学谱-光谱二维数据矩阵进行主成分分析，可确定化学反应过程存在的组分数。提出用优化动力学参数-减秩因子分析法解析二维数据矩阵，对未知动力学模型的复杂反应可同时优化求解第一步反应的级数和速率常数。模拟二维数据验证了该方法的可行性。该方法用于高锰酸钾氧化溴化钠的反应过程中测得的二维数据的解析，结果表明：高锰酸钾的还原过程符合0级反应模型。     

有机同秩物概念及单取代烷烃同秩物生成焓和电离能变化规律

提出了“有机同秩列”、“有机同秩物”、“有机同秩异构体”等概念体系,并以单取代烷烃同秩物Xi-（CH2）/-H（Xi=F、CI、Br、I、NO2、CN、NC、OH、NH2、SH、COOH、CHO）为例,对其气相标准摩尔生成焓（△rHm）、电离能（IP）的结构-性能关系进行了研究,分别对j=2～8的七组同秩物的生成焓及j=2～4的三组同秩物的电离能建立了数学模型：△rHm（j）=a＋b△iHm（1）＋cPEI（R）和IP（j）：a＋bIP（1）＋bPEI（R）,得到了有意义的结果．研究表明,从有机同秩物的角度可以建立一种新的分子结构．性能相关方法,它与有机同系物方法相互独立又互为补充．本文提出的概念体系不仅增加了新的有机化学理论和概念,还为有机物结构-性能变化规律的研究开辟了新视角．     

电化学聚合

介绍了电化学聚合反应的定义、分类,机理和应用,阐述了电化学缩合反应的电化学加成聚合反应这两大类电化学聚合反应的本质差别,另外还提出了电化学氰基加成聚合反应的概念。     

酸度分布-吸收光谱法用于灰色体系中食用色素的定量分析

利用合成色素随ｐＨ变化的人分布分数曲线和吸收光谱构成两维波谱信息,建立了灰色体系中色素的定量分析方法。约束背景双线性分解法（ＣＢＢＬ）结合数值遗传算法（ＮＧＡ）用于两维矩阵的数据处理。推导了型体总数与两维矩阵的有效秩之间的关系。吸光度矩阵的主成分数根据残余矩阵的残差平方和噪声水平相比较 确定,对标准样品及模拟灰色体系样品的研究表明该法确定的主成分数与理论值一致。对胭脂红、日落黄和柠檬黄的模拟灰色休     

铂电极上二茂铁甲基季铵盐电催化氧化异烟肼的电化学及其动力学性质研究

在0.1 mol·L-1Na2SO4水溶液中,二茂铁甲基季铵盐对异烟肼的电化学氧化具有很好的催化作用。运用循环伏安法研究了二茂铁甲基季铵盐和异烟肼的浓度、扫描速率分别对该电催化氧化体系的影响,同时运用循环伏安法和计时电流法探讨了该电催化氧化反应体系的电化学动力学规律,由电化学动力学测定并计算出了该催化体系的电子转移系数α、反应级数、催化反应速率常数k值。     

电化学合成乙酰基吡嗪北大核心CSCD

本文以吡嗪和丙酮酸为原料,在铅电极上电化学活化过硫酸铵得到的硫酸根自由基为氧化剂,首次采用电化学方法合成了乙酰基吡嗪。探究了电流密度、反应物摩尔比、反应物浓度、过硫酸铵、pH值对乙酰基吡嗪收率的影响,同时在外加硫酸亚铁的条件下探究复合活化法对收率的影响。在最优条件下(电流密度100 A·m^(-2),丙酮酸浓度0.33 mol·L^(-1),吡嗪浓度1.00 mol·L^(-1)),该反应的收率为44.12%。该工艺反应条件温和,简单易控,利用“清洁能源”电子代替了过渡金属盐以活化过硫酸铵,因而是一种环境友好的乙酰基吡嗪制备方法,具有广阔的工业化应用前景。     

动力学体系二维数据的秩分析及其应用

详细论证了动力学体系中存在的多种共线性情况,以及在此情况下二维数据阵的秩与独立反应数及组分数的关系.分析了通过增秩这一方式来判断体系组分数的条件.讨论了反应间存在物质交换对数据阵秩的影响.建立起一套通过秩分析判断未知动力学体系中存在的反应组分数、独立反应数以及可能反应机理的方法.将秩分析技术应用到聚苯胺与质子酸反应,初步分析了该体系存在的多种吸光性结构及结构变化.确定了[H＋]=0.01～0.1 mol•L－1范围内,聚苯胺与质子酸反应存在一个三结构两步互变过程.     

分光光度法同时测定多元素的研究(Ⅱ)——以CPA-矩阵法计算混合体系中微量锆和铪

本文将m-NPF+CTMAB体系用于锆、铪混合物中微量锆、铪的同时测定。确定了同时测定锆,铪的最佳实验条件。通过使用CPA-矩阵法计算解决了混合体系中锆、铪分量的测定;对光度分析中应用CPA-矩阵法的关键——选择适宜的测定波长问题作了进一步讨论,提出了“相关波长”和“相关组份”的概念。     

藏红T的电化学还原及其电生自由基的ESR跟踪研究

利用电化学方法和ESR(电子自旋共振)-电化学联用技术在无水乙醇体系中研究了藏红T(ST)的电化学还原行为。通过就地跟踪其1-电子还原的中间产物——自由基,推测了该自由基的结构。观察到ST电化学还原过程中存在着后续的、平行的零级和一级衰变反应。这一事实使有的电极反应与酶催化反应相关联的论点进一步得到实验的印证和支持。根据对不同浓度的ST溶液在不同还原电位下生成自由基行为研究结果,提出了ST在该溶液体系中的还原机理,并用曲线拟合法推算了反应历程中有关步骤的动力学参数。     

Accelerated stochastic simulation of the stiff enzyme-substrate reaction

The enzyme-catalyzed conversion of a substrate into a product is a common reaction motif in cellular chemical systems. In the three reactions that comprise this process, the intermediate enzyme-substrate complex is usually much more likely to decay into its original constituents than to produce a product molecule. This condition makes the reaction set mathematically "stiff." We show here how the simulation of this stiff reaction set can be dramatically speeded up relative to the standard stochastic simulation algorithm (SSA) by using a recently introduced procedure called the slow-scale SSA. The speedup occurs because the slow-scale SSA explicitly simulates only the relatively rare conversion reactions, skipping over occurrences of the other two less interesting but much more frequent reactions. We describe, explain, and illustrate this simulation procedure for the isolated enzyme-substrate reaction set, and then we show how the procedure extends to the more typical case in which the enzyme-substrate reactions occur together with other reactions and species. Finally, we explain the connection between this slow-scale SSA approach and the Michaelis-Menten [Biochem. Z. 49, 333 (1913)] formula, which has long been used in deterministic chemical kinetics to describe the enzyme-substrate reaction.     

自优化扩散量子Monte Carlo差值法

提出了自优化扩散量子MonteCarlo差值法,这是一个集优化、扩散和相关取样三项技术于一身的MonteCarlo新算法.这个算法能够在扩散过程中直接计算两个体系之间的能量差,且使计算结果的统计误差达到10^-5hartree数量级,获得相关能达80%以上.应用该方法研究分子势能面,使用"刚性移动"模型,利用Jacobi变换使分子两个几何构型的能量计算具有很好的正相关性,因而能得到准确的能量差值和分子势能面.另外,我们还首创了"平衡后留样"技术,可节省50%以上的计算量.该算法还可应用于分子光谱、化学反应能量变化值等领域的研究.     

Rank annihilation factor analysis for multicomponent kinetic‐spectrophotometric determination using difference spectra

In this work rank annihilation factor analysis (RAFA) is used to analyze difference spectra of kinetic‐spectrophotometric data. Annihilation of the contribution of one chemical component from the original data matrix is a general method in RAFA. However, sometimes RAFA is not suitable for studying rank deficient data such as kinetic‐spectrophotometric measurements. On the other hand, in order to apply RAFA for the determination of an analyte in an unknown sample, a standard two‐way matrix of the analyte with rank one should generally be available. This is not usually attainable for kinetic‐spectrophotometric monitoring of complexation reactions. Processes monitored by difference spectroscopy always have the spectrum of the initial stage subtracted from each spectrum in the data matrix. In this work we show that, for kinetic‐spectrophotometric data of complexation reactions, the spectrum of ligand (reactant) itself can be used as initial spectrum for subtraction. The obtained difference matrix of sample and that of analyte of interest will be full‐rank and rank 1, respectively. Therefore the system can be analyzed by RAFA. The proposed method was investigated with simulated data at the first stage. The method was then applied in the analysis of experimental kinetic‐spectrophotometric data of a complexation reactions of Co(II) and Ni(II) with chromogenic reagent 1‐(2‐pyridylazo) 2‐naphthol in order to do multi‐component determination of these ions in various real samples. Copyright © 2009 John Wiley & Sons, Ltd.     

Differential diffusion quantum Monte Carlo method: determination of potential energy surfaces of molecules

A differential approach for self-optimizing diffusion Monte Carlo calculation was proposed in this paper, which is a new algorithm combining three techniques such as optimizing, diffusion and correlation sampling. This method can be used to directly compute the energy differential between two systems in the diffusion process, making the statistical error of calculation be reduced to order of 10-5 hartree, and recover about more than 80% of the correlation energy. We employed this approach to set up a potential energy surface of a molecule, used a "rigid move" model, and utilized Jacobi transformation to make energy calculation for two configurations of a molecule having good positive correlation. So, an accurate energy differential could be obtained, and the potential energy surface with good quality can be depicted. In calculation, a technique called "post-equilibrium remaining sample was set up firstly, which can save about 50% of computation expense. This novel algorithm was used to study the potenti     

The Effective Permittivity of Reacting Mixture Solutions for Multiphysics Calculations

Huang and Yang (PIER Lett. 5: 99?C107, 2008) proposed a method based on experimental results to calculate the effective permittivity of liquid reacting mixture solutions. The method cannot be directly applied to multiphysics calculations for microwave heating on chemical reactions, because the derived formula of effective permittivity is a function of the reaction time. In this paper, we improve the method to obtain the effective permittivity as a function of the reactants?? concentrations and temperature by numerical fitting. Thus, the formula can be directly used for multiphysics calculation. Three measured effective permittivity curves for the iodination of acetone reaction under constant temperature were used to calculate the corresponding coefficients of the method at both 915?C2,450?MHz. The results calculated by the coefficients are in satisfactory agreement and approach the measured results.     

利用目标试验因子分析法确定化学反应的级数及速率常数

利用目标试验因子分析(TTFA)结合数值遗传算法(NGA).解析反应过程中在线测得的动力学谱-光谱数据矩阵,可在未知各组分纯光谱及动力学模型情况下同时求解出各组分的纯光谱、反应级数及速率常数。提出用近似计算法计算各组分的动力学谱,使该方法能适用于任意反应级数的体系。针对两步连续反应模型,对反应物、中间体和最终产物均有吸收及某一种组分没有吸收的体系的模拟实验数据矩阵进行了处理,表明该方法均能适用。利用该方法对邻苯二甲酸二甲酯在碱性介质中的水解反应及日落黄水溶液的电解降解反应过程中测得的数据矩阵进行解析,均获得了可靠结果。     

Accurate hybrid stochastic simulation of a system of coupled chemical or biochemical reactions

The dynamical solution of a well-mixed, nonlinear stochastic chemical kinetic system, described by the Master equation, may be exactly computed using the stochastic simulation algorithm. However, because the computational cost scales with the number of reaction occurrences, systems with one or more "fast" reactions become costly to simulate. This paper describes a hybrid stochastic method that partitions the system into subsets of fast and slow reactions, approximates the fast reactions as a continuous Markov process, using a chemical Langevin equation, and accurately describes the slow dynamics using the integral form of the "Next Reaction" variant of the stochastic simulation algorithm. The key innovation of this method is its mechanism of efficiently monitoring the occurrences of slow, discrete events while simultaneously simulating the dynamics of a continuous, stochastic or deterministic process. In addition, by introducing an approximation in which multiple slow reactions may occur within a time step of the numerical integration of the chemical Langevin equation, the hybrid stochastic method performs much faster with only a marginal decrease in accuracy. Multiple examples, including a biological pulse generator and a large-scale system benchmark, are simulated using the exact and proposed hybrid methods as well as, for comparison, a previous hybrid stochastic method. Probability distributions of the solutions are compared and the weak errors of the first two moments are computed. In general, these hybrid methods may be applied to the simulation of the dynamics of a system described by stochastic differential, ordinary differential, and Master equations.     

Determination of rank by median absolute deviation (DRMAD): a simple method for determining the number of principal factors responsible for a data matrix

Median absolute deviation (MAD) is a well‐established statistical method for determining outliers. This simple statistic can be used to determine the number of principal factors responsible for a data matrix by direct application to the residual standard deviation (RSD) obtained from principal component analysis (PCA). Unlike many other popular methods the proposed method, called determination of rank by MAD (DRMAD), does not involve the use of pseudo degrees of freedom, pseudo F‐tests, extensive calibration tables, time‐consuming iterations, nor empirical procedures. The method does not require strict adherence to normal distributions of experimental uncertainties. The computations are direct, simple to use and extremely fast, ideally suitable for online data processing. The results obtained using various sets of chemical data previously reported in the chemical literature agree with the early work. Limitations of the method, determined from model data, are discussed. An algorithm, written in MATLAB format, is presented in the Appendix. Copyright © 2008 John Wiley & Sons, Ltd.